City spatial structure and smart city innovation: the case of China
| DOI | https://doi.org/10.1108/IMDS-01-2022-0016 |
| Published date | 19 September 2022 |
| Date | 19 September 2022 |
| Pages | 2217-2236 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Yongtai Chen,Rui Li,En-yu Zeng,Pengfei Li |
City spatial structure and smart
city innovation: the case of China
Yongtai Chen
School of Information Engineering, Nanjing Audit University, Nanjing, China
Rui Li
School of Government Audit, Nanjing Audit University, Nanjing, China, and
En-yu Zeng and Pengfei Li
School of Engineering and Management, Nanjing University, Nanjing, China
Abstract
Purpose –This study aims to analyze the relevance of the city spatial structure for smart city innovation from
the perspective of agglomeration externalities, and discusses whether there is heterogeneity in innovation
across different geographical areas and population scales of cities.
Design/methodology/approach –The authors construct the centralization and concentration indexes to
conceptualize the city spatial structure of 286 cities (prefecture-level) in China based on the LandScan Global
Population Dataset from 2001 to 2016. A fixed-effects paneldata model is employed to analyze the relationship
between the spatial structure and the innovation ability of smart cities; the results were validated through
robustness tests and heterogeneity analyses.
Findings –The study found that the more concentratedand more evenly the distribution of urban population,
namely the more city spatial structure tends to be weak-monocentricity, the higher the level of innovation in
smart cities. The relevance of the weak-monocentricitystructure and smart city innovation varies significantly
depending on their geographical location and the size of the city. This result is more applicable to cities in the
eastern and central regions, as well as to cities with smaller populations.
Originality/value –The adjustment and optimization of the city spatial structure is important for enhancing
smart city construction. Unlike previous studies, which mostly use a single dimension of “the proportion of
population in sub-centres to the population of all central areas”to measure city spatial structure, the authors
employed the spatial centralization and spatial concentration. It is hoped that this study can guide smart city
construction from the perspective of the development model of city spatial structure.
Keywords Smart city, Spatial structure, Innovation performance
Paper type Research paper
1. Introduction
As an emerging city development strategy in the Internet era, smart city construction has
been gaining traction currently, especially among scholars. The concept of smart city is
derived from that of “Smart Planet,”which is a new social development model, proposed by
International Business Machines Corporation (IBM) in 2008. A smart city is an urban
governance concept and construction model that makes comprehensive use of information
technologies such as the Internet of things, cloud computing, big data analysis and spatial
geographic information integration to promote the wisdom of smart city planning,
construction, management and services.
In parallel with the development of smart city construction, research on smart cities has
been progressing, with most relevant studies focusing on the technical aspects and exploring
how to use emerging technologies to promote intelligent city development and achieve
sustainable development of smart cities (Singh et al., 2020). However, in the economic and
City spatial
structure and
city innovation
2217
This research was supported by the National Natural Science Foundation of China (Grant No. 92046022,
71872061), the Social Sciences Foundation of Jiangsu Province (Grant No. 19EYB020), the Postgraduate
Research & Practice Innovation Program of Jiangsu Province (Grant No. SJCX22_0929) and the Key
Program of NSFC-FRQSC Joint Project (NSFC No. 72061127002, FRQSC No. 295837).
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 10 January 2022
Revised 4 May 2022
28 June 2022
23 August 2022
Accepted 24 August 2022
Industrial Management & Data
Systems
Vol. 122 No. 10, 2022
pp. 2217-2236
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-01-2022-0016
social fields, research on smart cities is mostly qualitative and demonstrates a lack of
empirical analysis. The extant literature on smart cities primarily focuses on the
characteristics and evaluation index system of smart cities, paying more attention to the
problems, risks and challenges in the process of smart city construction (Rong et al., 2014).
Meanwhile, research on innovation capacity in the construction of smart cities is minimal.
The innovation factor is usually considered as a driver and determinant of economic
development and an important indicator for evaluating and assessing the development of a
city’s construction (Mackinnon et al., 2002;Sim-mie,2004). Innovation is oftenseen as the most
importantdriver of economic development,and a high level of city innovationcan significantly
boost the development of a smart economy and,in turn, a smart city. Considering the ongoing
constructionof smart cities in newcountries, includingChina, the question of how to effectively
improve technological innovation in smartcities is a matter of concern.
According to an earlier theoretical study, innovation isviewed as operating at the firm or
individual level, and past theoretical studies have focused on how factors such as social and
human capital (McGuirk et al.,2015) and research and development (R&D) investment
(Rodr
ıguez-Pose and Crescenzi, 2008) act on innovation. Recent studies have shown that
innovationis also a product of cities and regions(Florida et al.,2017).Innovation outcomes are
not so much anoutput as individuals or firms,but rather a product of citiesand regions, which
bring together the means of production, a rich diversity of talent, infrastructure and other
required inputs for innovative and entrepreneurial activity. In essence, innovation and
creativityare not simply processes at the individualor firm level, but more typically processes
at the city and regionallevel. Therefore, identifyingthe city spatial structure conduciveto the
constructionof smart cities is crucial to promotethe development of innovationin smart cities.
The existingstudies on city spatialstructure mainly focuson its association with city economic
growth (Meijers and Burger, 2010), environmental pollution management (Wang et al.,2017)
and traffic congestion (Li et al., 2019),but the topic of city spatial structureand the innovation
ability in the context of smart cities has been rarely addressed.
After announcing the first batch of smart city pilots [1] in 2012, the Chinese government
announced a new batch of smart city pilots in August 2013 and April 2015, subsequently
promulgating a series of related policies to assist the development of smart city construction.
It might be argued that the smart city construction currently underway in China provides an
excellent sample for the study of the relationship between city spatial structure and smart
city innovation. Therefore, taking China as an example, this study focuses on examining the
relevance of the city spatial structure for smart city innovation, exploring which city
structure is more conducive to the innovative development of smart cities and providing
policy recommendations for the construction of smart cities in China and new countries
around the world. To this end, we focus on the following research questions:
RQ1. What kind of city spatial structure is chosen in the process of smart city
construction, the better the innovation capacity of the smart city?
RQ2. Is innovationin smart cities heterogeneousacross geographicregions and city sizes?
The remainder of this paper is organized as follows. An overview of the literature related to
city structure and innovation is provided in Section 2. Following this, the methodology of this
case study and research hypotheses are described in Section 3. Further, the estimation results
and robustness checks are presented in Section 4, followed by the conclusions in Section 5.
2. Literature review
Currently, although there is no conclusive definition of what constitutes a smart city
(Camero and Alba, 2019), the implementation of smart cities is still steadily progressing.
IMDS
122,10
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